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Device-level power electronic circuit simulation is so cumbersome that engineers are forced to make model simplification or reduce circuit size to obtain a reasonable execution time for repeated simulation runs. This paper proposes a massive-thread parallel simulation of large-scale power electronic circuits employing device-level modeling on the graphics processors (GPUs) to obtain higher data throughput and lower execution times. Parallel massive-thread modules are proposed for the nonlinear physics-based insulated gate bipolar transistor and power diode components. The nonlinear solution algorithm comprised of Newton–Raphson iterations and partial LU decomposition is fully parallelized on the GPU. Furthermore, the commonly used behavioral model with reduced computational complexity is also employed to represent the switches. The developed simulation codes are used to run large-scale test cases of the modular multilevel converter (MMC) system. The accuracy and efficiency of the GPU-based parallel simulation are compared with sequential CPU-based codes and the SaberRD program to show the advantages of the parallelized simulation; execution time speedups of 15 times and 70 times are reported for the MMC system using the nonlinear physics-based modeling and behavior-based modeling, respectively. [ABSTRACT FROM AUTHOR]

The electromagnetic transient (EMT) simulation of a large-scale power system consumes so much computational power that parallel programming techniques are urgently needed in this area. For example, realistic-sized power systems include thousands of buses, generators, and transmission lines. Massive-thread computing is one of the key developments that can increase the EMT computational capabilities substantially when the processing unit has enough hardware cores. Compared to the traditional CPU, the graphic-processing unit (GPU) has many more cores with distributed memory which can offer higher data throughput. This paper proposes a massive-thread EMT program (MT-EMTP) and develops massive-thread parallel modules for linear passive elements, the universal line model, and the universal machine model for offline EMT simulation. An efficient node-mapping structure is proposed to transform the original power system admittance matrix into a block-node diagonal sparse format to exploit the massive-thread parallel GPU architecture. The developed MT-EMTP program has been tested on large-scale power systems of up to 2458 three-phase buses with detailed component modeling. The simulation results and execution times are compared with mainstream commercial software, EMTP-RV, to show the improvement in performance with equivalent accuracy. [ABSTRACT FROM AUTHOR]

This paper proposes large-scale transient stability simulation based on the massively parallel architecture of multiple graphics processing units (GPUs). A robust and efficient instantaneous relaxation (IR)-based parallel processing technique which features implicit integration, full Newton iteration, and sparse LU-based linear solver is used to run the multiple GPUs simultaneously. This implementation highlights the combination of coarse-grained algorithm-level parallelism with fine-grained data-parallelism of the GPUs to accelerate large-scale transient stability simulation. Multithreaded parallel programming makes the entire implementation highly transparent, scalable, and efficient. Several large test systems are used for the simulation with a maximum size of 9,984 buses and 2,560 synchronous generators all modeled in detail resulting in matrices that are larger than 20\,000\times 20\,000. [ABSTRACT FROM AUTHOR]